Hierarchical Shrinkage Stan Models for Biomarker Selection

---

Documentation for package ‘hsstan’ version 0.8.2

• DESCRIPTION file.
• Package NEWS.

Help Pages

hsstan-package	Hierarchical shrinkage Stan models for biomarker selection
bayes_R2	Bayesian and LOO-adjusted R-squared
bayes_R2.hsstan	Bayesian and LOO-adjusted R-squared
diabetes	Diabetes data with interaction terms
hsstan	Hierarchical shrinkage models
kfold	K-fold cross-validation
kfold.hsstan	K-fold cross-validation
log_lik	Pointwise log-likelihood
log_lik.hsstan	Pointwise log-likelihood
loo	Predictive information criteria for Bayesian models
loo.hsstan	Predictive information criteria for Bayesian models
loo_R2	Bayesian and LOO-adjusted R-squared
loo_R2.hsstan	Bayesian and LOO-adjusted R-squared
nsamples	Number of posterior samples
nsamples.hsstan	Number of posterior samples
plot.projsel	Plot of relative explanatory power of predictors
posterior_interval	Posterior uncertainty intervals
posterior_interval.hsstan	Posterior uncertainty intervals
posterior_linpred	Posterior distribution of the linear predictor
posterior_linpred.hsstan	Posterior distribution of the linear predictor
posterior_performance	Posterior measures of performance
posterior_predict	Posterior predictive distribution
posterior_predict.hsstan	Posterior predictive distribution
posterior_summary	Posterior summary
posterior_summary.default	Posterior summary
posterior_summary.hsstan	Posterior summary
print.hsstan	Print a summary for the fitted model
projsel	Forward selection minimizing KL-divergence in projection
sampler.stats	Sampler statistics
summary.hsstan	Summary for the fitted model
waic	Predictive information criteria for Bayesian models
waic.hsstan	Predictive information criteria for Bayesian models